Electronic article surveillance (“EAS”) systems are detection systems that allow the identification of a marker, tag or label within a given detection zone. EAS systems have many uses, but most often they are used as security systems for preventing shoplifting in stores or removal of property in office buildings. EAS systems come in many different forms and make use of a number of different technologies.
A typical EAS system includes an electronic detection unit, tags, labels and/or markers, and a detacher or deactivator. The detection units can, for example, be formed as pedestal units, buried under floors, mounted on walls, or hung from ceilings. The detection units are usually placed in high traffic areas, such as entrances and exits of stores or office buildings. The tags, labels and/or markers have special characteristics and are specifically designed to be affixed to or embedded in merchandise or other objects sought to be protected. When an active tag passes through a tag detection zone, the EAS system sounds an alarm, a light is activated and/or some other suitable alert devices are activated to indicate the removal of the tag from the prescribed area.
Common EAS systems operate with these same general principles using either transceivers, which each transmit and receive, or a separate transmitter and receiver. Typically the transmitter is placed on one side of the detection zone and the receiver is placed on the opposite side of the detection zone. The transmitter produces a predetermined excitation signal in a tag detection zone. In the case of a retail store, this detection zone is usually formed at an exit. When an EAS tag enters the detection zone, the tag has a characteristic response to the excitation signal, which can be detected. For example, the tag may respond to the signal sent by the transmitter by using a simple semiconductor junction, a tuned circuit composed of an inductor and capacitor, soft magnetic strips or wires, or vibrating magneto acoustic resonators. The receiver subsequently detects this characteristic response. By design, the characteristic response of the tag is distinctive and not likely to be created by natural circumstances.
An consideration in connection with the use of such EAS systems is to minimize the occurrence of false alarms which could either cause embarrassment to customers of an EAS system user, e.g., a retail store, or produce annoying and disruptive alarm signals when no one is passing through the store's EAS system or when a tag has not been properly deactivated.
Failure to deactivate (“FTD”) is a major complaint affecting all EAS detection platforms. This undesirable side effect poses a serious confidence issue to system users, who inadvertently grow accustomed to “deactivated” tags triggering an alarm, thus, ignoring valid alarm events where live tags are involved. This phenomenon occurs when a tag, or label, is not properly deactivated and still carries some properties of a live tag, mainly a spectral (frequency) property. Theoretically, the natural frequency (characteristic frequency) of a live tag is approximately 58 kHz. Consequently, many detection platforms are designed to have approximate operating frequencies of 57.8 kHz to 58.2 kHz. When a tag is properly deactivated, its characteristic frequency is typically shifted to the 60 kHz range, to effectively place the tag outside of the desired frequency detection range, and thus the tag can no longer trigger an alarm event. A partially deactivated or “wounded” tag, however, can have its characteristic frequency shifted to the 59 kHz range and can potentially be detected, especially if the tag's energy is large enough at its new spectral (frequency) attribute. Statistically, about 10%-15% of tags being deactivated are really only wounded tags that are not thoroughly neutralized, and therefore result in relatively high occurrence of FTD events for system users.
Attempts to resolve the FTD issue have included digital frequency estimators using a Tabei and Musicus technique, which is a very complex algorithm that produces nonlinear output responses. Frequency estimators suffer from a phenomenon referred to as “threshold effect”. Threshold effect occurs when a frequency estimator performs satisfactorily above some minimum input signal-to-noise ratio (“SNR”), but degrades very rapidly below that minimum SNR. This problem is amplified by the fact that the frequency estimator must operate on the raw input signal, and a low minimum SNR will bring about inconsistent zero crossing points. These zero crossing points are the basis for the Tabei and Musicus technique and eventually lead to undependable frequency estimations. Therefore, a FTD criterion based on a frequency estimator is unreliable and leads to a high rate of false alarms caused by tags that have not been properly deactivated.
What is needed is a method and system that can be used to inhibit detection of deactivated tags in a detection system.